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Interplay between Physical Layer Security and Blockchain Technology for 5G and Beyond: A Comprehensive Survey

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TechRxiv

TechRxiv 2022年

作者： Ghourab, Esraa M. Jaafar, Wael Bariah, Lina Naser, Shimaa Muhaidat, Sami Yanikomeroglu, Halim The KU Center for Cyber-Physical Systems Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates The Department of Software and Information Technology Engineering Ecole de Technologie Supérieure MontrealQCH3C 1K3 Canada Abu Dhabi9639 United Arab Emirates The Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada The Department of Systems and Computer Engineering Carleton University OttawaON Canada

Fifth-generation and beyond (5G and xG) wireless networks are envisioned to meet the requirements of vertical applications like high traffic throughput, ultra-massive connectivity, extremely low latency, and high quality of service. Disruptive technologies, such as massive multiple-input multiple-output, millimeter wave, and multiple access are being deployed to meet these requirements. However, their deployment poses several challenges, including a lack of network transparency, management decentralization, and reliability. Moreover, the heterogeneity of future networks raises security concerns, e.g., confidentiality, privacy, and trustworthiness. Indeed, due to the emergence of novel paradigms, e.g., quantum computing, traditional security approaches are no longer sufficient to protect over-the-air communications. Hence, 5G/xG networks must consider smart security techniques to operate seamlessly and efficiently. Within this context, physical layer security (PLS) and blockchain represent promising solutions to complement existing methods. By exploiting the characteristics of wireless links, PLS can enhance the security of communications, while blockchain may enable networks’ decentralization, integrity, and trustworthiness. Motivated by these advancements, we provide an in-depth review of the existing PLS and blockchain literature. Then, for the first time in the literature, we present a framework to integrate PLS with blockchain in 5G/xG systems. We first provide a thorough discussion about the potential of PLS and blockchain for 5G/xG systems. Then, we present our vision of a cross-layer architecture that leverages PLS and blockchain. Through a case study, we demonstrate the high potential of cross-layer design to improve the security of vehicular networks. Finally, we identify related challenges and shed light on future research directions. © 2022, CC BY.

关键词： MIMO systems

Achieving Enhanced Security in Biometric Authentication: A Rigorous Analysis of Code-Based Fuzzy Extractor 10

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Achieving Enhanced Security in Biometric Authentication: A R...

10th International Scientific Conference "Information Technology and Implementation", IT and I 2023

作者： Kuznetsov, Oleksandr Frontoni, Emanuele Kuznetsova, Yelyzaveta Smirnov, Oleksii Chevardin, Vladyslav Department of Political Sciences Communication and International Relations University of Macerata Via Crescimbeni 30/32 Macerata62100 Italy Department of Information and Communication Systems Security School of Computer Sciences V. N. Karazin Kharkiv National University 4 Svobody Sq. Kharkiv61022 Ukraine Department of Information Engineering Marche Polytechnic University Via Brecce Bianche 12 Ancona60131 Italy Department of cyber security and software Central Ukrainian National Technical University 8 University Ave Kropyvnytskyi25006 Ukraine Military Institute of Telecommunications and Information Technologies Moskovska str. 45/1 Kiev01015 Ukraine

In the contemporary digital era, the intersectionality between biometric authentication and cryptographic security has emerged as a pivotal research domain, particularly in the context of facial recognition. This study embarks on a meticulous exploration of code-based fuzzy extractors, delving into their theoretical underpinnings and practical applications within biometric authentication systems. Through a comprehensive examination of False Rejection Rate (FRR) and False Acceptance Rate (FAR) metrics, the research illuminates the delicate balance and trade-offs inherent in optimizing security while ensuring user-friendly interactions. The study juxtaposes theoretical predictions with empirical findings, revealing notable disparities and highlighting the complexities and unpredictabilities embedded within real-world biometric data. Furthermore, the research navigates through the Receiver Operating Characteristic (ROC) curves, providing a nuanced understanding of the interplay between FRR and FAR, and its implications on system performance and reliability. While the findings offer a foundational framework and insights into the potentialities and challenges of implementing fuzzy extractors in biometric authentication, they also underscore the necessity for continuous exploration and development, especially in the context of post-quantum cryptographic resilience and real-world applicability. The study, while providing a stepping stone, invites further research and development to navigate the evolving challenges and potentials that permeate the dynamic landscape of biometric authentication and cryptographic systems. © 2023 Copyright for this paper by its authors.

关键词： Economic and social effects

Compromised ACC vehicles can degrade current mixed-autonomy traffic performance while remaining stealthy against detection

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arXiv 2021年

作者： Gunter, George Li, Huichen Hojjati, Avesta Nice, Matthew Bunting, Matthew Gunter, Carl A. Li, Bo Sprinkle, Jonathan Work, Daniel The Department of Civil and Environmental Engineering The Institute for Software Integrated Systems Vanderbilt University TN United States The Department of Electrical and Computer Engineering The Institute for Software Integrated Systems Vanderbilt University TN United States The Department of Computer Science University of Illinois at Urbana-Champaign IL United States The Department of Computer and Electrical Engineering University of Arizona AZ United States

We demonstrate that a supply-chain level compromise of the adaptive cruise control (ACC) capability on equipped vehicles can be used to significantly degrade system level performance of current day mixed-autonomy freeway networks. Via a simple threat model which causes random deceleration attacks (RDAs), compromised vehicles create congestion waves in the traffic that decrease average speed and network throughput. We use a detailed and realistic traffic simulation environment to quantify the impacts of the attack on a model of a real high-volume freeway in the United States. We find that the effect of the attack depends both on the level of underlying traffic congestion, and what percentage of ACC vehicles can be compromised. In moderate congestion regimes the attack can degrade mean commuter speed by over 7%. In high density regimes overall network throughput can be reduced by up to 3%. And, in moderate to high congestion regimes, it can cost commuters on the network over 300 kmhrUSD. All of these results motivate that the proposed attack is able to significantly degrade performance of the traffic network. We also develop an anomaly detection technique that uses GPS traces on vehicles to identify malicious/compromised vehicles. We employ this technique on data from the simulation experiments and find that it is unable to identify compromised ACCs compared to benign/normal drivers. That is, these attacks are stealthy to detection. Stronger attacks can be accurately labeled as malicious, motivating that there is a limit to how impactful attacks can be before they are no longer stealthy. Finally, we experimentally execute the attack on a real and commercially available ACC vehicle, demonstrating the possible real world feasibility of an RDA. In particular, we test two well-known CAN bus detection techniques on the ensuing data and find that they fail to identify the malicious messages, suggesting that the attacks may be stealthy to detection at the vehicular level as

关键词： Anomaly detection

Energy-Efficient Data Offloading for Earth Observation Satellite Networks

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Energy-Efficient Data Offloading for Earth Observation Satel...

IEEE Conference on Vehicular Technology (VTC)

作者： Lijun He Ziye Jia Juncheng Wang Feng Wang Erick Lansard Chau Yuen School of Software Northwestern Polytechnical University China Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics China Department of Computer Science Hong Kong Baptist University China Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Electrical and Electronics Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

In Earth Observation Satellite Networks (EOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving the data offloading efficiency. As such, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in EOSNs, aiming to balance the objectives of reducing the total energy consumption and increasing the sum weights of tasks. First, we derive the optimal power allocation solution to the joint optimization problem when the task scheduling policy is given. Second, leveraging the conflict graph model, we transform the original joint optimization problem into a maximum weight independent set problem when the power allocation strategy is given. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the sum weights of tasks and the total energy consumption, thus achieving superior system performance over the current best alternatives.

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Energy-Efficient Data Offloading for Earth Observation Satellite Networks

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arXiv 2024年

作者： He, Lijun Jia, Ziye Wang, Juncheng Wang, Feng Lansard, Erick Yuen, Chau School of Software Northwestern Polytechnical University China Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics China Department of Computer Science Hong Kong Baptist University China Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Electrical and Electronics Engineering Nanyang Technological University Singapore

In Earth Observation Satellite Networks (EOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving the data offloading efficiency. As such, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in EOSNs, aiming to balance the objectives of reducing the total energy consumption and increasing the sum weights of tasks. First, we derive the optimal power allocation solution to the joint optimization problem when the task scheduling policy is given. Second, leveraging the conflict graph model, we transform the original joint optimization problem into a maximum weight independent set problem when the power allocation strategy is given. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the sum weights of tasks and the total energy consumption, achieving superior system performance over the current best alternatives. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy utilization

Mechanical Vibrations on a Deployable Nanosatellite Antenna: SAR Performance Analysis

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Mechanical Vibrations on a Deployable Nanosatellite Antenna:...

European Conference on Antennas and Propagation, EuCAP

作者： Andrew C. M. Austin Timothy Pelham Simone Mencarelli Annalisa Tresoldi Mohammed Dabboor Guglielmo Aglietti Michael J. Neve Communication Systems and Networks Group University of Bristol Bristol UK Department of Electrical Computer and Software Engineering University of Auckland Auckland New Zealand Te Pūnaha Ātea—Auckland Space Institute University of Auckland Auckland New Zealand Science and Technology Branch Environment and Climate Change Canada Dorval QC Canada

The mechanical vibrations of a high-strain glass-fibre composite deployable X-band synthetic aperture radar (SAR) antenna structure are investigated using a finite element method. The antenna is approximately $\mathrm{2}\ \mathrm{m}\times \mathrm{0}.\mathrm{3}\ \mathrm{m}$ , and exhibits natural frequencies at 2.8 Hz and 7.6 Hz. The radiation patterns for a reflectarray formed from the structure are calculated using a ray-tracing approach for the nominal and mechanically deformed cases. The mechanically deformed antenna pattern is defocused, and a SAR system model shows this reduces the signal-to-noise ratio of a point scattering target by approximately 6 dB.

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Training Differentially Private Models with Secure Multiparty Computation

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arXiv 2022年

作者： Pentyala, Sikha Railsback, Davis Maia, Ricardo J.M. Melanson, David Dowsley, Rafael Nascimento, Anderson De Cock, Martine School of Engineering and Technology University of Washington Tacoma United States Department of Computer Science University of Brasilia Brazil Department of Software Systems and Cybersecurity Monash University Australia Department of Applied Mathematics Computer Science and Statistics Ghent University Belgium Mila - Quebec Ai Institute Canada

We address the problem of learning a machine learning model from training data that originates at multiple data owners, while providing formal privacy guarantees regarding the protection of each owner's data. Existing solutions based on Differential Privacy (DP) achieve this at the cost of a drop in accuracy. Solutions based on Secure Multiparty Computation (MPC) do not incur such accuracy loss but leak information when the trained model is made publicly available. We propose an MPC solution for training DP models. Our solution relies on an MPC protocol for model training, and an MPC protocol for perturbing the trained model coefficients with Laplace noise in a privacy-preserving manner. The resulting MPC+DP approach achieves higher accuracy than a pure DP approach, while providing the same formal privacy guarantees. Our work obtained first place in the iDASH2021 Track III competition on confidential computing for secure genome analysis. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

Physics-informed Inverse Design of Multi-bit Programmable Metasurfaces

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arXiv 2024年

作者： Xu, Yucheng Yang, Jia-Qi Fan, Kebin Wang, Sheng Wu, Jingbo Zhang, Caihong Zhan, De-Chuan Padilla, Willie J. Jin, Biaobing Chen, Jian Wu, Peiheng Key Laboratory of Optoelectronic Devices and Systems with Extreme Performances of MOE School of Electronic Science and Engineering Nanjing University Nanjing210023 China Purple Mountain Laboratories Nanjing211111 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China Department of Electrical and Computer Engineering Duke University Box 90291 DurhamNC27708 United States

Emerging reconfigurable metasurfaces offer various possibilities in programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270o, due to the design constraints with time-intensive forward design methodologies. Here, we demonstrate a multi-bit programmable metasurface capable of terahertz beam steering, facilitated by a developed physics-informed inverse design (PIID) approach. Through integrating a modified coupled mode theory (MCMT) into residual neural networks, our PIID algorithm not only significantly increases the design accuracy compared to conventional neural networks but also elucidates the intricate physical relations between the geometry and the modes. Without decreasing the reflection intensity, our method achieves the enhanced phase tuning as large as 300o. Additionally, we experimentally validate the inverse designed programmable beam steering metasurface, which is adaptable across 1-bit, 2-bit, and tri-state coding schemes, yielding a deflection angle up to 68o and broadened steering coverage. Our demonstration provides a promising pathway for rapidly exploring advanced metasurface devices, with potentially great impact on communication and imaging technologies. © 2024, CC0.

关键词： Tuning

A Modified Symbiotic Organism Search Algorithm with Lévy Flight for software Module Clustering Problem 5th

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A Modified Symbiotic Organism Search Algorithm with Lévy Fl...

5th International Conference on Electrical, Control and computer engineering, InECCE 2019

作者： Zainal, Nurul Asyikin Zamli, Kamal Z. Din, Fakhrud Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Gambang KuantanPahang26300 Malaysia Department of Computer Science & IT University of Malakand Khyber Pakhtunkhwa Pakistan

ISBN: (纸本)9789811523168

To date, there are much increasing trends on adopting parameter free meta-heuristic algorithms for solving general optimization problems. With parameter free algorithms, there are no parameter controls for tuning. As such, the adoption of parameter free meta-heuristic algorithms is often straightforward. On the negative note, exploration (i.e. roaming the search space thoroughly) and exploitation (i.e. manipulating the current known best neighbor) are pre-set. As the search spaces are problem dependent, any pre-set exploration and exploitation can lead to entrapment in local optima. In this paper, we investigate the use of Lévy flight to enhance the exploration of a parameter free meta-heuristic algorithm, called Modified Symbiotic Organism Search Algorithm (MSOS), via its population initialization. Our experimentations involving the software module clustering problems have been encouraging, as MSOS gives competitive results against existing selected parameter free meta-heuristic algorithms. For all the given module clustering problems, MSOS generates overall best mean results. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms